Biology subjects

Li, C.

Publications and source records attributed to Li, C..

At least 829 records · Page 46Linked to original sources

bioRxiv2021

A human ensemble cell atlas (hECA) enables in data cell sorting

Single-cell omics data can characterize multifaceted features of massive cells and bring significant insights to biomedical researches. The accumulation of single-cell data provides growing resources for constructing atlases for all cells of a human organ or the whole body. The true assembly of a cell atlas should be cell-centric rather than file-centric. We proposed a unified information framework enabling seamless cell-centric data assembly and developed a human Ensemble Cell Atlas (hECA) as an instance. hECA version 1.0 assembled scRNA-seq data across multiple studies into one orchestrated data repository. It contains 1,093,299 labeled cells and metadata from 116 published human single-cell studies, covering 38 human organs and 11 systems. We invented three methods of applications based on the cell-centric assembly: "In data" cell sorting enables targeted data retrieval in the full atlas with customizable logic expressions; The "quantitative portraiture" system provides a multi-view presentation of biological entities (organs, cell types, and genes) of multiple granularities; The customizable reference creation allows users to use the cell-centric assembly to generate references for their own cell type annotations. Case studies on agile construction of user-defined sub-atlases and "in data" investigation of CAR-T off-targets in multiple organs showed the great potential of cell-centric atlas assembly.

bioinformatics↗

bioRxiv2021

High-throughput production of functional prototissues capable of producing NO for vasodilation

Bottom-up synthesis of prototissues helps us to understand the internal cellular communications in the natural tissues and their functions, as well as to improve or repair the damaged tissues. The existed prototissues are rarely used to improve the function of living tissues. We demonstrated a methodology to produce spatially programmable prototissues based on the magneto-Archimedes effect in a high-throughput manner. More than 2000 prototissues are produced once within 2 hours. Two-component and three-component spatial coded prototissues are fabricated by varying the addition giant unilamellar vesicles (GUVs) order/number, and the magnetic field distributions. Two-step and three-step signal communications in the prototissues are realized using cascade enzyme reactions. More importantly, the two-component prototissues capable of producing nitric oxide (NO) cause vasodilation of rat blood vessels in the presence of glucose and hydroxyurea. The tension force decreases 2.59 g, meanwhile the blood vessel relaxation is of 31.2%. Our works pave the path to fabricate complicated programmable prototissues, and hold great potential in tissue transplantation in the biomedical field.

bioengineering↗

bioRxiv2021

A Quantitative Paradigm for Water Assisted Proton Transport Through Proteins and Other Confined Spaces

Water assisted proton transport through confined spaces influences many phenomena in biomolecular and nanomaterial systems. In such cases, the water molecules that fluctuate in the confined pathways provide the environment and the medium for the hydrated excess proton migration via Grotthuss shuttling. However, a definitive collective variable (CV) that accurately couples the hydration and the connectivity of the proton wire with the proton translocation has remained elusive. To address this important challenge - and thus to define a new quantitative paradigm for facile proton transport in confined spaces - a CV is derived in this work from graph theory, which is verified to accurately describe water wire formation and breakage coupled to the proton translocation in carbon nanotubes and the Cl-/H+ antiporter protein, ClC-ec1. Significant alterations in the conformations and thermodynamics of water wires are uncovered after introducing an excess proton into them. Large barriers in the proton translocation free energy profiles are found when water wires are defined to be disconnected according to the new CV, even though the pertinent confined space is still reasonably well hydrated and - by the simple measure of the mere existence of a water structure - the proton transport would have been predicted to be facile via that oversimplified measure. In this new paradigm, however, the simple presence of water is not sufficient for inferring proton translocation since an excess proton itself is able to drive hydration and, additionally, the water molecules themselves must be adequately connected to facilitate any successful proton transport. Significance StatementAs first proposed more than 200 years ago by Grotthuss, proton transport is enabled by a chemical bond-breaking and bond-making proton hopping mechanism through water networks or "wires", often contained within confined systems such as protein channels or nanotubes. Herein, concepts from graph theory are utilized in order to define a new continuously differentiable collective variable (CV) for water wire connectivity and facile proton transport. As such, the water connectivity can be explicitly quantified via free energy sampling, to both qualitatively and quantitatively describe the thermodynamics and kinetics of water-facilitated proton transport via Grotthuss hopping - something that has been lacking since the first conceptual identification of this key chemical process in Nature.

biophysics↗

bioRxiv2021

LENG8 regulation of mRNA processing, is responsible for the control of mitochondrial activity

The processing of mRNA is essential for the maintenance of cellular and tissue homeostasis. However, the precise regulation of this process in mammalian cells, remains largely unknown. Here we have found that LENG8 represents the mammalian orthologue of the yeast mRNA processing factor Thp3 and Sac3. We go on to demonstrate that LENG8 binds to mRNAs, associates with components of mRNA processing machinery (the TREX complex) and contributes to mRNA nuclear export to the cytoplasm. Loss of LENG8, leads to aberrant accumulation of poly (A)+ RNA in the nucleus, in both Hela cells and murine fibroblasts. Furthermore, the precipitation of LENG8, is associated with an enrichment of both mRNAs and lncRNAs, and approximately half of these are also bound by the TREX component, THOC1. However, LENG8 preferentially binds mRNAs encoding for mitochondrial proteins and depletion of this processing factor, causes a dramatic breakdown in mitochondrial ultrastructure and a reduction in mitochondrial respiratory activity. Conditional deletion of Leng8 in mouse adipose tissues lead to a decreased body weight, and increased adipose thermogenesis. Our work has found an evolutionarily conserved mRNA processing factor that can control mitochondrial activity.

cell biology↗

bioRxiv2021

Inactivation effects of plasma-activated water on Fusarium graminearum

The continuous usage of fungicides poses a potential threat to the environment, ranging from mere irritation to being very toxic to human beings and organisms. Plasma-activated water (PAW) has recently gained much interest as a promising candidate to inactivate fungi. However, the inactivation mechanisms of PAW are still not well understood. In this study, the effect of PAW on the viability and the cellular responses of Fusarium graminearum in PAW inactivation were investigated. The results showed that microbial activity of spores was significantly inhibited by PAW treatment (P < 0.05). The symptoms caused by F. graminearum were significantly reduced on the spikelets. Our data indicated that PAW could induce cell wall sculpturing, membrane permeability changes, and mitochondrial dysfunction. Differential gene expression analysis also confirmed that the cell membrane, the cell wall and the mitochondria were the organelles most affected by PAW. The results from this study facilitate the understanding of the mechanisms underlying the responses of F. graminearum to PAW and the development of PAW as a potential fungicidal agent or an effective supplement to fungicides. HighlightsO_LIThe viability of F. graminearum is notably inhibited by PAW C_LIO_LIThe symptoms caused by F. graminearum were significantly reduced on the spikelets C_LIO_LIOxidative stress induce cell wall sculpturing, membrane permeability change C_LIO_LIPAW can cause the mitochondrial dysfunction C_LIO_LICell wall, membrane and mitochondria are the most affected organelles by PAW C_LI

microbiology↗

bioRxiv2021

Reciprocal regulation of Shh trafficking and H2O2 levels via a noncanonical BOC-Rac1 pathway

Among molecules that bridge environment, cell metabolism, and cell signaling, H2O2 recently appeared as an emerging but central player. Its level depends on cell metabolism and environment and was recently shown to play key roles during embryogenesis, contrasting with its long-established role in disease progression. We decided to explore whether the secreted morphogen Sonic hedgehog (Shh), known to be essential in a variety of biological processes ranging from embryonic development to adult tissue homeostasis and cancers, was part of these interactions. Here, we report that H2O2 levels control key steps of Shh delivery and that physiological in vivo modulation of H2O2 levels changes Shh distribution and tissue patterning. A feedback loop exists in which Shh trafficking controls H2O2 synthesis via a non-canonical BOC-Rac1 pathway, leading to cytoneme growth. Our findings reveal that Shh directly impacts its own distribution, thus providing a molecular explanation for the robustness of morphogenesis to both environmental insults and individual variability.

cell biology↗

bioRxiv2021

Dynamics of glioma-associated microglia and macrophages reveals their divergent roles in the immune response of brain

Glioma microenvironment contains numerous myeloid cells, including brain-resident microglia and recruited monocytes and macrophages (Mo/M{varphi}). When studied collectively, these cells presented pro-tumor effects. Yet, little is known about the differences among these myeloid populations. Using single-cell sequencing analysis, we studied the phenotypic characteristics, spatial variances, and dynamic changes of these relatively heterogeneous cell populations. Microglia populations with distinct spatial distribution presented different functional states, including tumor-associated subsets with phagocytic and lipid metabolism signature. Notably, this subset of glioma-associated microglia shared similar trait in a diverse spectrum of neuropathogenesis. In contrast, Mo/M{varphi} highly expressed genes related to angiogenesis, tumor invasion, and immune evasion. Moreover, identifying the Mo/M{varphi} subsets had prognostic and classificatory value in clinical application. These results thus eliminate the long-existing ambiguity about the role of microglia and Mo/M{varphi} in glioma pathogenesis, and reveal their prognostic and therapeutic value for glioma patients.

immunology↗

bioRxiv2021

Critical Assessment of Metagenome Interpretation - the second round of challenges

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the community-driven initiative for the Critical Assessment of Metagenome Interpretation (CAMI). In its second challenge, CAMI engaged the community to assess their methods on realistic and complex metagenomic datasets with long and short reads, created from [~]1,700 novel and known microbial genomes, as well as [~]600 novel plasmids and viruses. Altogether 5,002 results by 76 program versions were analyzed, representing a 22x increase in results. Substantial improvements were seen in metagenome assembly, some due to using long-read data. The presence of related strains still was challenging for assembly and genome binning, as was assembly quality for the latter. Taxon profilers demonstrated a marked maturation, with taxon profilers and binners excelling at higher bacterial taxonomic ranks, but underperforming for viruses and archaea. Assessment of clinical pathogen detection techniques revealed a need to improve reproducibility. Analysis of program runtimes and memory usage identified highly efficient programs, including some top performers with other metrics. The CAMI II results identify current challenges, but also guide researchers in selecting methods for specific analyses.

bioinformatics↗

bioRxiv2021

Mapping the host protein interactome of non-coding regions in SARS-CoV-2 genome

A deep understanding of SARS-CoV-2-host interactions is crucial to the development of effective therapeutics. The role of non-coding regions of viral RNA (ncrRNAs) has not been scrutinized. We developed a method using MS2 affinity purification coupled with liquid chromatography-mass spectrometry (MAMS) to systematically map the interactome of SARS-CoV-2 ncrRNA in different human cell lines. Integration of the results defined the core and cell-type-specific ncrRNA-host protein interactomes. The majority of ncrRNA-binding proteins were involved in RNA biogenesis, protein translation, viral infection, and stress response. The 5' UTR interactome is enriched with proteins in the snRNP family and is a target for the regulation of viral replication and transcription. The 3' UTR interactome is enriched with proteins involved in the cytoplasmic RNP granule (stress granule) and translation regulation. We show that the ORF10 is likely to be a part of 3' UTR. Intriguingly, the interactions between negative-sense ncrRNAs and host proteins, such as translation initiation factors and antiviral factors, suggest a pathological role of negative-sense ncrRNAs. Moreover, the cell-type-specific interactions between ncrRNAs and mitochondria may explain the differences of cell lines in viral susceptibility. Our study unveils a comprehensive landscape of the functional SARS-CoV-2 ncrRNA-host protein interactome, providing a new perspective on virus-host interactions and the design of future therapeutics.

genomics↗

bioRxiv2021

X-DPI: A structure-aware multi-modal deep learning model for drug-protein interactions prediction

MotivationIdentifying the drug-protein interactions (DPIs) is crucial in drug discovery, and a number of machine learning methods have been developed to predict DPIs. Existing methods usually use unrealistic datasets with hidden bias, which will limit the accuracy of virtual screening methods. Meanwhile, most DPIs prediction methods pay more attention to molecular representation but lack effective research on protein representation and high-level associations between different instances. To this end, we presented here a novel structure-aware multi-modal DPIs prediction model, X-DPI, performing on a curated industry-scale benchmark dataset. ResultsWe built a high-quality benchmark dataset named GalaxyDB for DPIs prediction. This industry-scale dataset along with an unbiased training procedure resulted in a more robust benchmark study. For informative protein representation, we constructed a structure-aware graph neural network method from the protein sequence by combining predicted contact maps and graph neural networks. Through further integration of structure-based representation and high-level pre-trained embeddings for molecules and proteins, our model captured more effectively the feature representation of the interactions between them. As a result, X-DPI outperformed state-of-the-art DPIs prediction methods and obtained 5.30% Mean Square Error (MSE) improved in the DAVIS dataset and 8.89% area under the curve (AUC) improved in GalaxyDB dataset. Moreover, our model is an interpretable model with the transformer-based interaction mechanism, which can accurately reveal the binding sites between molecule and protein.

bioinformatics↗

bioRxiv2021

OsciDrop: A versatile on-demand droplet generator

Droplet microfluidics is a powerful tool in many biological and clinical applications. Microfluidic chips, such as flow-focusing droplet generators, have been extensively used to high-throughput encapsulate reactions with single-cell and single-molecular resolutions. However, microfabrication is expensive and precision-demanding, preventing it from widespread use in biomedical laboratories and clinical facilities. Herein, we present a versatile chip-free droplet generator, OsciDrop, for generating size-tunable droplets on demand, with high uniformity. OsciDrop segments the fluid flowing out of the orifice of a micropipette tip into droplets by oscillating the tip under the surface of a continuous oil phase. We investigated the factors influencing droplet generation by examining several control parameters. Results show that flow rate, oscillating amplitude, and frequency are key parameters to generate monodisperse droplets on demand. And OsciDrop is able to generate droplets in a flexible and repeatable manner. Importantly, using an optimal asymmetrical oscillation waveform, OsciDrop can controllably generate monodisperse droplets spanning a wide volume range (200 pL - 2 L). To demonstrate the ability of OsciDrop for chip-free droplet assays, a digital loop-mediated isothermal amplification (dLAMP) was performed to absolutely quantify African swine fever virus (ASFV). The OsciDrop method opens up a feasible and versatile avenue to perform droplet-based assays, exhibiting full accessibility for chip-free droplet microfluidics.

bioengineering↗

bioRxiv2021

A novel and accurate full-length HTT mouse model for Huntington's disease

Here we report the generation and characterization of a novel Huntingtons disease (HD) mouse model BAC226Q by using a bacterial artificial chromosome (BAC) system, expressing full-length human HTT with [~]226 CAG-CAA repeats and containing endogenous human HTT promoter and regulatory elements. BAC226Q recapitulated a full-spectrum of age-dependent and progressive HD-like phenotypes without unwanted and erroneous phenotypes. BAC226Q mice developed normally, and gradually exhibited HD-like mood and cognitive phenotypes at 2 months. From 3-4 months, BAC226Q mice showed robust progressive motor deficits. At 11 months, BAC226Q mice showed significant reduced life span, gradual weight loss and exhibit neuropathology including significant brain atrophy specific to striatum and cortex, striatal neuronal death, widespread huntingtin inclusions and reactive pathology. Therefore, the novel BAC226Q mouse accurately recapitulating robust, age-dependent, progressive HD-like phenotypes will be a valuable tool for studying disease mechanisms, identifying biomarkers and testing gene-targeting therapeutic approaches for HD.

neuroscience↗

bioRxiv2021

scSVAS: CNV clonal visualization online platform for large scale single-cell genomics

The recent advance of single-cell copy number variation analysis plays an essential role in addressing intra-tumor heterogeneity, identifying tumor subgroups, and restoring tumor evolving trajectories at single-cell scale. Pleasant visualization of copy number analysis results boosts productive scientific exploration, validation, and sharing. Several single-cell analysis figures have the effectiveness of visualizations for understanding single-cell genomics in published articles and software packages. However, they almost lack real-time interaction, and it is hard to reproduce them. Moreover, existing tools are time-consuming and memory-intensive when they reach large-scale single-cell throughputs. We present an online visualization platform, scSVAS, for real-time interactive single-cell genomics data visualization. scSVAS is specifically designed for large-scale single-cell analysis. Compared with other tools, scSVAS manifests the most comprehensive functionalities. After uploading the specified input files, scSVAS deploys the online interactive visualization automatically. Users may make scientific discoveries, share interactive visualization, and download high-quality publication-ready figures. scSVAS provides versatile utilities for managing, investigating, sharing, and publishing single-cell copy number variation profiles. We envision this online platform will expedite the biological understanding of cancer clonal evolution in single-cell resolution. All visualizations are publicly hosted at https://sc.deepomics.org.

bioinformatics↗

bioRxiv2021

Endogenous RNA editing of a nuclear gene BOSS triggers flowering in tomato

RNA editing is defined as the production of transcripts with RNA sequences different from those of the DNA template. Most of previous RNA editing studies have focused on organelles, while RNA editing of nuclear transcripts is largely unknown. Here, we describe the first example of nuclear transcript RNA editing in plant, the BOSS RNA editing regulates tomato flowering. The SNP (SNP1) located in the 5UTR of BOSS gene (the Balancer of SP and SFT) is associated with tomato early flowering, and two transcripts of BOSS produced by SNP1 associated RNA editing show functional differentiation, where BOSS-{beta} transcript promotes flowering while BOSS- does not. Furthermore, these two transcripts of BOSS are shown to regulate SP (anti-florigen) pathway at transcription level in the shoot apical meristem (SAM). Our findings reveal a new layer of complexity in the control of plant stem cell proliferation and provide the evidence of RNA-editing of a single gene for flowering, suggesting that molecular breeding programs to increase the RNA-editing efficiency may improve the productivity of tomatoes and other agricultural organisms.

plant biology↗

bioRxiv2021

Loss of Acta2 in cardiac fibroblasts does not affect myofibroblast differentiation or cardiac repair after myocardial infarction

In response to myocardial infarction (MI), quiescent cardiac fibroblasts differentiate into myofibroblasts mediating tissue repair in the infarcted area. One of the most widely accepted markers of myofibroblast differentiation is the expression of Acta2 which encodes smooth muscle alpha-actin (SMA) that is assembled into stress fibers. However, the requirement of Acta2 in the myofibroblast differentiation of cardiac fibroblasts and its role in post-MI cardiac repair were still not known. To answer these questions, we generated a tamoxifen-inducible cardiac fibroblast-specific Acta2 knockout mouse line. Surprisingly, mice that lacked Acta2 in cardiac fibroblasts had a normal survival rate after MI. Moreover, Acta2 deletion did not affect the function or overall histology of infarcted hearts. No difference was detected in the proliferation, migration, or contractility between WT cardiac fibroblasts and Acta2-null cardiac myofibroblasts. Additional analysis identified that Acta2-null cardiac myofibroblasts had a normal total filamentous actin level and total actin level. Acta2 deletion caused a unique compensatory increase in the transcription level of Actg2 and a possible increase in the protein abundance of cytoplasmic actin isoforms. In conclusion, the deletion of Acta2 does not prevent the myofibroblast differentiation of cardiac fibroblasts or affect the post-MI cardiac repair, and the increase in the expression of non-SMA actin isoforms and the functional redundancy between actin isoforms are likely able to compensate for the loss of Acta2 in cardiac myofibroblasts.

molecular biology↗

bioRxiv2021

DENIES: A deep learning based two-layer predictor for enhancing the identification of enhancers and their strength with DNA shape information

The identification of enhancers has always been an important task in bioinformatics owing to their major role in regulating gene expression. For this reason, many computational algorithms devoted to enhancer identification have been put forward over the years. To boost the performance of their methods, more features are extracted from the single DNA sequences and integrated to develop an ensemble classifier. Nevertheless, the sequence-derived features used in previous studies can hardly provide the 3D structure information of DNA sequences, which is regarded as an important factor affecting the binding preferences of transcription factors to regulatory elements like enhancers. Given that, we here propose SENIES, a DNA shape enhanced deep learning predictor, for the identification of enhancers and their strength. The predictor consists of two layers where the first layer is for enhancer and non-enhancer identification, and the second layer is for predicting the strength of enhancers. Besides utilizing two common sequence-derived features (i.e. one-hot and k-mer) as input, it introduces DNA shape for describing the 3D structures of DNA sequences. Performance comparison with state-of-the-art methods conducted on the same datasets demonstrates the effectiveness and robustness of our method. The code implementation of our predictor is publicly available at https://github.com/hlju-liye/SENIES.

bioinformatics↗

bioRxiv2021

The First High-Quality Reference Genome of Sika Deer Provides Insights for High-Tannin Adaptation

Sika deer are known to prefer oak leaves, which are rich in tannins and toxic to most mammals; however, the genetic mechanisms underlying their unique ability to adapt to living in the jungle are still unclear. In identifying the mechanism responsible for the tolerance of a highly toxic diet, we have made a major advancement in the elucidation of the genomics of sika deer. We generated the first high-quality, chromosome-level genome assembly of sika deer and measured the correlation between tannin intake and RNA expression in 15 tissues through 180 experiments. Comparative genome analyses showed that the UGT and CYP gene families are functionally involved in the adaptation of sika deer to high-tannin food, especially the expansion of UGT genes in a subfamily. The first chromosome-level assembly and genetic characterization of the tolerance toa highly toxic diet suggest that the sika deer genome will serve as an essential resource for understanding evolutionary events and tannin adaptation. Our study provides a paradigm of comparative expressive genomics that can be applied to the study of unique biological features in non-model animals.

genomics↗

bioRxiv2021

Fluorescence-Activated Droplet Sorting of Polyethylene terephthalate Degrading Enzymes

Enzymes that can decompose synthetic plastics such as polyethylene terephthalate (PET) are urgently needed. However, a bottleneck remains due to a lack of techniques for detecting and sorting environmental microorganisms with vast diversity and abundance. Here, we developed a fluorescence-activated droplet sorting (FADS) pipeline for high-throughput screening of PET-degrading microorganisms or enzymes (PETases). The pipeline comprises three steps: generation and incubation of droplets encapsulating single cells, picoinjection of fluorescein dibenzoate (FDBz) as the fluorogenic probe, and screening of droplets to obtain PET-degrading cells. We characterized critical factors associated with this method, including specificity and sensitivity for discriminating PETase from other enzymes. We then optimized its performance and compatibility with environmental samples. The system was used to screen a wastewater sample from a PET textile mill. We successfully obtained PET-degrading species from nine different genera. Moreover, two putative PETases from isolates Kineococcus endophyticus Un-5 and Staphylococcus epidermidis Un-C2-8 were genetically derived, heterologously expressed, and preliminarily validated for PET-degrading activities. We speculate that the FADS pipeline can be widely adopted to discover new PET-degrading microorganisms and enzymes in various environments and may be utilized in the directed evolution of PETases using synthetic biology.

microbiology↗